Designer materials: Entropy can lead to order, paving the route to nanostructures

Shapes can arrange themselves into crystal structures through entropy alone, new research from the University of Michigan shows. Image credit: P. Damasceno, M. Engel, S. Glotzer

(Phys.org) -- Researchers trying to herd tiny particles into useful ordered formations have found an unlikely ally: entropy, a tendency generally described as "disorder."

Computer simulations by University of Michigan scientists and engineers show that the property can nudge particles to form organized structures. By analyzing the shapes of the particles beforehand, they can even predict what kinds of structures will form.

The findings, published in this week's edition of Science, help lay the ground rules for making designer materials with wild capabilities such as shape-shifting skins to camouflage a vehicle or optimize its aerodynamics.

Physicist and chemical engineering professor Sharon Glotzer proposes that such materials could be designed by working backward from the desired properties to generate a blueprint. That design can then be realized with nanoparticlesparticles a thousand times smaller than the width of a human hair that can combine in ways that would be impossible through ordinary chemistry alone.

One of the major challenges is persuading the nanoparticles to create the intended structures, but recent studies by Glotzer's group and others showed that some simple particle shapes do so spontaneously as the particles are crowded together. The team wondered if other particle shapes could do the same.

"We studied 145 different shapes, and that gave us more data than anyone has ever had on these types of potential crystal-formers," Glotzer SAID. "With so much information, we could begin to see just how many structures are possible from particle shape alone, and look for trends."

Using computer code written by chemical engineering research investigator Michael Engel, applied physics graduate student Pablo Damasceno ran thousands of virtual experiments, exploring how each shape behaved under different levels of crowding. The program could handle any polyhedral shape, such as dice with any number of sides.

Left to their own devices, drifting particles find the arrangements with the highest entropy. That arrangement matches the idea that entropy is a disorder if the particles have enough space: they disperse, pointed in random directions. But crowded tightly, the particles began forming crystal structures like atoms doeven though they couldn't make bonds. These ordered crystals had to be the high-entropy arrangements, too.

Glotzer explains that this isn't really disorder creating orderentropy needs its image updated. Instead, she describes it as a measure of possibilities. If you could turn off gravity and empty a bag full of dice into a jar, the floating dice would point every which way. However, if you keep adding dice, eventually space becomes so limited that the dice have more options to align face-to-face. The same thing happens to the nanoparticles, which are so small that they feel entropy's influence more strongly than gravity's.

"It's all about options. In this case, ordered arrangements produce the most possibilities, the most options. It's counterintuitive, to be sure," Glotzer said.

The simulation results showed that nearly 70 percent of the shapes tested produced crystal-like structures under entropy alone. But the shocker was how complicated some of these structures were, with up to 52 particles involved in the pattern that repeated throughout the crystal.

The particle shapes produced three crystal types: regular crystals like salt, liquid crystals as found in some flat-screen TVs and plastic crystals in which particles can spin in place. By analyzing the shape of the particle and how groups of them behave before they crystallize, Damasceno said that it is possible to predict which type of crystal the particles would make.

"The geometry of the particles themselves holds the secret for their assembly behavior," he said.

Why the other 30 percent never formed crystal structures, remaining as disordered glasses, is a mystery.

"These may still want to form crystals but got stuck. What's neat is that for any particle that gets stuck, we had other, awfully similar shapes forming crystals," Glotzer said.

In addition to finding out more about how to coax nanoparticles into structures, her team will also try to discover why some shapes resist order.

Related Stories

(PhysOrg.com) -- In a study that elevates the role of entropy in creating order, research led by the University of Michigan shows that certain pyramid shapes can spontaneously organize into complex quasicrystals.

The method to the madness of quasicrystals has been a mystery to scientists. Quasicrystals are solids whose atoms aren't arranged in a repeating pattern, as they are in ordinary crystals. Yet they form intricate patterns ...

University of Michigan researchers have discovered a way to self-assemble nanoparticles into wires, sheets, shells and other unusual structures using sticky patches that make the particles group themselves together in programmed ...

Scientists have long studied how atoms and molecules structure themselves into intricate clusters. Unlocking the design secrets of Nature offers lessons in engineering artificial systems that could self-assemble into any ...

Nature is a master builder. Using a bottom-up approach, nature takes tiny atoms and, through chemical bonding, makes crystalline materials, like diamonds, silicon and even table salt. In all of them, the properties of the ...

Microscopic particles are being coaxed by Duke University engineers to assemble themselves into larger crystalline structures by the use of varying concentrations of microscopic particles and magnetic fields.

Recommended for you

Chemotherapy is often used as a follow-up treatment after surgical removal of a cancerous tumor in order to destroy any remaining cancer cells, but intravenous chemo drugs have notorious side effects and are not always effective.

A research team at the Center for Nanoparticle Research, within the Institute for Basic Science (IBS), has developed a wearable and implantable device that measures electrophysiological signals and applies electrical and ...

Dr. Giordano Mattoni, quantum researcher at TU Delft, and his collaborators have shown that the nano-electronic phase transition in a class of materials known as nickelates can be controlled by laser light. Their findings, ...

The discovery of buckyballs surprised and delighted chemists in the 1980s, nanotubes jazzed physicists in the 1990s, and graphene charged up materials scientists in the 2000s, but one nanoscale carbon structure—a negatively ...

Tuning materials for optimal optical and electrical properties is becoming commonplace. Now, researchers and manufacturers may be able to tune materials for thermal conductivity by using a squid-inspired protein made of multiple ...

3 comments

Good for astrobiology! Besides throwing a monkey wrench into the creationist machinery for disfiguring entropy, it neatly answers my pet peeve when people equates entropy, whether macrostate or microstate, with some loose form of disorder:

Instead, she describes it as a measure of possibilities.

That is what I use: "Entropy (as a microstate fine-grained parameter) is a measure of the availability of states." Over time the tendency for more available energy states, a higher entropy, would ratchet up if it can, purely for probabilistic reasons.

As this physics tells us, whether those states are more ordered or disordered depends on the details of the system.

TL; DR: Entropy =/= disorder.

Entropy may have helped the first cells to form, entropy forces is a (small, IIRC) part of what makes micelles and later membrane protocells assemble. It may even today be part of what constitutes the cell construction.

They forgot to account for many factors I've mentioned elsewhere, or example, since this is a simulation and therefore a nested reality, they forgot to account for the entropy in the "more fundamental" reality, being the real world. That is to say, the computer uses a certain amount of electricity and produces a certain amount of work on the particles, whilst producing a certain amount of heat waste. The computer creates, updates, and destroys countless temporary variables during the course of simulation, all of which represent "work" being done on the particles, as well as the associated heat waste and entropy not counted by the model itself.

Thus the computer, a machine, is doing "work" in the classical sense, on the data representing the particles, and they are not "spontaneously" assembling themselves, seeing as how classical work in a more fundamental level of reality is being done in order to accomplish the simulation.